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University Pension Plan

Intern Analyst, Active Public Markets (May 2027 - August 2027)

RBC north tower, Canada

  • Internship
  • Internship
  • Hybrid

About the role

THE ROLE

We are actively looking for an Intern Analyst, Active Public Markets, to join our team for a 4-month internship (May 2027 – August 2027). This role will be part of a growing and dynamic Investment team, reporting to the Associate Director of Quantitative Research, Public Markets. The incumbent will be responsible for helping support the development of the Public Markets portfolio management framework, with a specific focus on building, improving and data feeding monitoring tools across the three asset classes: public equity, public credit, and absolute return.

This is a fantastic opportunity for an undergraduate student to gain valuable work experience in a fast-growing, dynamic environment while being a part of a new pension plan.

This role is based in downtown Toronto in a hybrid work environment, allowing employees the flexibility to work remotely and in-office (minimum two days per week in-office).

Application Details: We ask that you submit a one-page resume, cover letter and transcript as part of the application process.

SPECIFIC ACCOUNTABILITIES

Support the development of data engineering pipelines and analytical tools.

Assist in quantitative analyses of investment managers under the guidance of senior team members to help inform evaluation and portfolio decisions.

Contribute to research on generative AI use cases that could enhance productivity in external portfolio management.

Collaborate with Investment team members to help with documentation reviews, system setup, and implementation of business processes and technology solutions

Perform basic ad-hoc data analysis and reporting to support ongoing investment projects and key decision-making.

QUALIFICATIONS & EXPERIENCE

Strong skills in software development and statistical analysis

Passion for capital markets

Academically rigorous coursework (e.g., quantitative courses in-progress or completed)

Knowledge and working experience with Large Language Model/Agentic AI is strongly preferred

ATTRIBUTES

Independent problem solver

Analytical, adaptive, multi-tasker, who has a strong work ethic and leadership skills

High degree of self-motivation and professionalism

Strong oral and written communication skills

Detail oriented with great statistical and quantitative skills